What is this?

This notebook contains a set of analyses for analyzing nakedmeeple’s boardgamegeek collection. The bulk of the analysis is focused on building a user-specific predictive model to predict the games that the specified user is likely to own. This enables us to ask questions like, based on the games the user currently owns, what games are a good fit for their collection? What upcoming games are they likely to purchase?

1 The Data

1.1 Collection Overview

We can look at a basic description of the number of games that the user owns, has rated, has previously owned, etc.

1.2 Collection by Year Published

What years has the user owned/rated games from? While we can’t see when a user added or removed a game from their collection, we can look at their collection by the years in which their games were published.

1.3 What types of games does nakedmeeple own?

We can look at the most frequent types of categories, mechanics, designers, and artists that appear in a user’s collection.

2 Modeling nakedmeeple’s Collection

We’ll examine predictive models trained on a user’s collection for games published through 2020. How many games has the user owned/rated/played in the training set (games prior to 2020)?

username	dataset	period	games_owned	games_rated
nakedmeeple	training	published before 2020	559	295
nakedmeeple	validation	published 2020	24	6
nakedmeeple	test	published after 2020	11	0

The main outcome we will be modeling for the user is owned, which refers to whether the user currently owns or has a previously owned a game in their collection. Our goal is to train a predictive model to learn the probability that a user will add a game to their collection based on its observable features. This amounts to looking at historical data and looking to find patterns that exist between features of games and games present in the user’s collection.

2.1 Decision Tree for nakedmeeple

One of the models we trained was a decision tree, which looks for decision rules that can be used to separate games the user owns from games they don’t. The resulting model produces a decision corresponding to yes or no statements: to explain why the model predicts the user to own game, we start at the top of the tree and follow the rules that were learned from the training data.

Note: the tree below has been further pruned to make it easier to visualize.

Decision trees are highly interpretible models that are easy to train and can identify important interactions and nonlinearities present in the data. Individual trees have the drawback of being less predictive than other common models, but it can be useful to look at them to gain some understanding of key predictors and relationships found in the training data.

2.2 Coefficients for nakedmeeple

We can examine coefficients from another model we trained, which is a logistic regression with elastic net regularization (which I will refer to as a penalized logistic regression). Positive values indicate that a feature increases a user’s probability of owning/rating a game, while negative values indicate a feature decreases the probability. To be precise, the coefficients indicate the effect of a particular feature on the log-odds of a user owning a game.

2.3 Visualizing Predictors

Why did the model identify these features? We can make density plots of the important features for predicting whether the user owned a game. Blue indicates the density for games owned by the user, while grey indicates the density for games not owned by the user.

Binary predictors can be difficult to see with this visualization, so we can also directly examine the percentage of games in a user’s collection with a predictor vs the percentage of all games with that predictor.

	% of Games with Feature
nakedmeeple	ZMan Games	9.8%	1.2%	8.03
nakedmeeple	GMT Games	8.4%	1.1%	7.39
nakedmeeple	Rio Grande Games	9.1%	1.7%	5.21
nakedmeeple	Eaglegryphon Games	3.6%	0.7%	5.18
nakedmeeple	Games With Solitaire Rules	21.6%	4.8%	4.53
nakedmeeple	Economic	27.2%	6.4%	4.23
nakedmeeple	Asmodee	9.3%	2.4%	3.80
nakedmeeple	Fantasy Flight Games	3.8%	1.1%	3.37
nakedmeeple	3D	3.6%	1.4%	2.55
nakedmeeple	Ravensburger	5.7%	2.4%	2.40
nakedmeeple	Dice Rolling	28.6%	28.3%	1.01
nakedmeeple	Scenario Mission Campaign Game	2.0%	2.1%	0.95
nakedmeeple	Trading	2.5%	3.0%	0.83
nakedmeeple	Fantasy	6.3%	12.1%	0.52
nakedmeeple	Miniatures Game	2.0%	4.9%	0.40
nakedmeeple	Video Game Theme	0.0%	1.6%	0.00

3 Examine Model’s Performance on Training Set

Before predicting games in upcoming years, we can examine how well the model did and what games it liked in the training set. In this case, we used resampling techniques (cross validation) to ensure that the model had not seen a game before making its predictions.

3.1 Top Games from Training Set

Displaying the 100 games from the training set with the highest probability of ownership, highlighting in blue games the user has owned.

Rank	Published	ID	Name	Pr(Owned)	Owned
1	2013	143693	Glass Road	0.999	yes
2	2015	175878	504	0.989	no
3	2011	70919	Takenoko	0.982	yes
4	2017	220308	Gaia Project	0.977	no
5	2019	270971	Era: Medieval Age	0.974	no
6	1999	552	Bus	0.970	yes
7	2008	35677	Le Havre	0.967	yes
8	2010	62219	Dominant Species	0.963	yes
9	2010	70512	Luna	0.960	yes
10	2010	62227	Labyrinth: The War on Terror, 2001 – ?	0.958	yes
11	2017	193728	Pendragon: The Fall of Roman Britain	0.956	yes
12	2007	31260	Agricola	0.953	yes
13	2016	200680	Agricola (Revised Edition)	0.949	no
14	2014	159675	Fields of Arle	0.946	yes
15	2019	274364	Watergate	0.946	yes
16	2014	164928	Orléans	0.945	no
17	2019	286096	Tapestry	0.944	no
18	2011	70149	Ora et Labora	0.941	yes
19	2009	39683	At the Gates of Loyang	0.932	yes
20	2010	73439	Troyes	0.929	yes
21	2017	232988	The Castles of Burgundy: The Dice Game	0.925	no
22	2002	4098	Age of Steam	0.924	yes
23	2016	163154	Falling Sky: The Gallic Revolt Against Caesar	0.923	yes
24	2012	120677	Terra Mystica	0.921	yes
25	2019	276025	Maracaibo	0.920	yes
26	2012	111341	The Great Zimbabwe	0.911	yes
27	2000	475	Taj Mahal	0.905	yes
28	2014	159508	AquaSphere	0.903	yes
29	2019	253635	Ragusa	0.901	no
30	2014	146886	La Granja	0.898	yes
31	2016	167791	Terraforming Mars	0.897	yes
32	2009	55670	Macao	0.897	yes
33	2007	28720	Brass: Lancashire	0.887	yes
34	2016	177736	A Feast for Odin	0.881	yes
35	1997	42	Tigris & Euphrates	0.877	yes
36	2017	221805	Breaking Bad: The Board Game	0.877	no
37	2011	108687	Puerto Rico	0.869	yes
38	2017	199904	Pericles: The Peloponnesian Wars	0.868	yes
39	2019	220558	Ancient Civilizations of the Inner Sea	0.860	no
40	2016	191977	The Castles of Burgundy: The Card Game	0.858	yes
41	2002	3076	Puerto Rico	0.846	no
42	2017	199383	Calimala	0.842	no
43	2019	256960	Pax Pamir: Second Edition	0.841	yes
44	2011	84876	The Castles of Burgundy	0.840	yes
45	2018	199792	Everdell	0.840	no
46	2018	233080	Book of Dragons	0.834	no
47	2004	9216	Goa	0.833	yes
48	2016	176083	Hit Z Road	0.831	no
49	2012	122515	Keyflower	0.828	yes
50	2007	25554	Notre Dame	0.823	yes
51	2007	31594	In the Year of the Dragon	0.819	no
52	2018	244711	Newton	0.818	no
53	2007	27173	Vikings	0.818	no
54	1999	875	Roads & Boats	0.816	yes
55	2014	145371	Three Kingdoms Redux	0.811	yes
56	2015	175914	Food Chain Magnate	0.808	yes
57	1999	88	Torres	0.806	yes
58	2016	159692	Comanchería: The Rise and Fall of the Comanche Empire	0.805	yes
59	2010	66505	The Speicherstadt	0.802	yes
60	2018	247763	Underwater Cities	0.791	yes
61	2010	25292	Merchants & Marauders	0.790	yes
62	2006	25613	Through the Ages: A Story of Civilization	0.785	no
63	2014	148228	Splendor	0.782	yes
64	2013	144041	Patchistory	0.780	no
65	2012	128780	Pax Porfiriana	0.772	yes
66	2017	226254	The Ruhr: A Story of Coal Trade	0.768	no
67	1999	204	Stephenson's Rocket	0.766	yes
68	2019	257066	Sierra West	0.766	no
69	2014	144189	Fire in the Lake	0.765	yes
70	2017	216132	Clans of Caledonia	0.762	no
71	2013	137408	Amerigo	0.757	yes
72	2019	256730	Pipeline	0.751	yes
73	2018	256916	Concordia Venus	0.739	no
74	2016	169786	Scythe	0.734	no
75	2016	165872	Liberty or Death: The American Insurrection	0.731	yes
76	1995	93	El Grande	0.727	no
77	2015	173346	7 Wonders Duel	0.726	no
78	2012	91080	Andean Abyss	0.720	yes
79	2012	119391	Il Vecchio	0.717	no
80	2017	161533	Lisboa	0.716	yes
81	1998	3	Samurai	0.713	yes
82	2017	233078	Twilight Imperium: Fourth Edition	0.711	no
83	2011	102680	Trajan	0.710	yes
84	2011	91873	Strasbourg	0.710	yes
85	2013	124361	Concordia	0.707	yes
86	2007	27708	1960: The Making of the President	0.707	yes
87	2001	878	Wyatt Earp	0.704	no
88	2019	285984	Last Bastion	0.703	no
89	2019	283863	The Magnificent	0.702	no
90	2018	214887	CO₂: Second Chance	0.693	yes
91	2018	245638	Coimbra	0.693	yes
92	2018	245928	Pax Emancipation	0.688	no
93	2016	193739	Jórvík	0.684	no
94	2010	66362	Glen More	0.683	yes
95	2008	37380	Roll Through the Ages: The Bronze Age	0.680	no
96	2012	119890	Agricola: All Creatures Big and Small	0.676	no
97	2015	181687	The Pursuit of Happiness	0.670	no
98	2005	11825	Empire of the Sun	0.668	no
99	2014	154825	Arkwright	0.666	yes
100	2018	244049	Forum Trajanum	0.664	no

3.2 Model Evaluation

This section contains a variety of visualizations and metrics for assessing the performance of the model(s) during resampling. If you’re not particularly interested in predictive modeling, skip down further to the predictions from the model.

3.2.1 Separation Plots

An easy way to examine the performance of classification model is to view a separation plot. We plot the predicted probabilities from the model for every game (from resampling) from lowest to highest. We then overlay a blue line for any game that the user does own. A good classifier is one that is able to separate the blue (games owned by the user) from the white (games not owned by the user), with most of the blue occurring at the highest probabilities (right side of the chart).

3.2.2 Area Under the Curve

We can more formally assess how well each model did in resampling by looking at the area under the receiver operating characteristic curve. A perfect model would receive a score of 1, while a model that cannot predict the outcome will default to a score of 0.5. The extent to which something is a good score depends on the setting, but generally anything in the .8 to .9 range is very good while the .7 to .8 range is perfectly acceptable.

wflow_id	.metric	.estimator	.estimate
GLM	roc_auc	binary	0.91
Decision Tree	roc_auc	binary	0.80

3.2.3 Lift and Gain Curve

Another way to think about the model performance is to view its lift, or its ability to detect the positive outcomes over that of a null model. High lift indicates the model can much more quickly find all of the positive outcomes (in this case, games owned or played by the user), while a model with no lift is no better than random guessing. A gains chart is another way to view this.

3.2.4 Optimal Cutpoint and Confusion Matrix

While we are probably more interested in the lift provided by the models to evaluate their efficacy, we can also explore the optimal cutpoint if we wanted to define a hard threshold for identifying games a user will own vs not own.

The threshold we select depends on how we much we care about false positives (games the model predicts that the user does not own) vs false negatives (games the user owns that the model does not predict). We can toggle threshold to

3.2.5 Calibration

Finally, we can understand the performance of the model by examining its calibration. If the model assigns a probability of 5%, how often does the outcome actually occur? A well calibrated model is one in which the predicted probabilities reflect the probabilities we would observe in the actual data. We can assess the calibration of a model by grouping its predictions into bins and assessing how often we observe the outcome versus how often our model expects to observe the outcome.

A model that is well calibrated will closely follow the dashed line - its expected probabilities match that of the observed probabilities. A model that consistently underestimates the probability of the event will be over this dashed line, be a while a model that overestimates the probability will be under the dashed line.

3.3 Most and Least Likely Games

What games does the model think nakedmeeple is most likely to own that are not in their collection?

Published	ID	Name	Pr(Owned)	Owned
2015	175878	504	0.989	no
2017	220308	Gaia Project	0.977	no
2019	270971	Era: Medieval Age	0.974	no
2016	200680	Agricola (Revised Edition)	0.949	no
2014	164928	Orléans	0.945	no

What games does the model think nakedmeeple is least likely to own that are in their collection?

Published	ID	Name	Pr(Owned)	Owned
1960	148203	Dutch Blitz	0.002	yes
2009	46213	Telestrations	0.002	yes
1992	327	Loopin' Louie	0.002	yes
2012	124708	Mice and Mystics	0.003	yes
2015	180974	Potion Explosion	0.003	yes

3.4 Top Games by Year

Top 25 games most likely to be owned by the user in each year, highlighting in blue the games that the user has owned.

rank	2012	2013	2014	2015	2016	2017	2018	2019
1	Terra Mystica	Glass Road	Fields of Arle	504	Agricola (Revised Edition)	Gaia Project	Everdell	Era: Medieval Age
2	The Great Zimbabwe	Patchistory	Orléans	Food Chain Magnate	Falling Sky: The Gallic Revolt Against Caesar	Pendragon: The Fall of Roman Britain	Book of Dragons	Watergate
3	Keyflower	Amerigo	AquaSphere	7 Wonders Duel	Terraforming Mars	The Castles of Burgundy: The Dice Game	Newton	Tapestry
4	Pax Porfiriana	Concordia	La Granja	The Pursuit of Happiness	A Feast for Odin	Breaking Bad: The Board Game	Underwater Cities	Maracaibo
5	Andean Abyss	Legacy: The Testament of Duke de Crecy	Three Kingdoms Redux	Mombasa	The Castles of Burgundy: The Card Game	Pericles: The Peloponnesian Wars	Concordia Venus	Ragusa
6	Il Vecchio	Impulse	Splendor	Haspelknecht: The Story of Early Coal Mining	Hit Z Road	Calimala	Coimbra	Ancient Civilizations of the Inner Sea
7	Agricola: All Creatures Big and Small	Cuba Libre	Fire in the Lake	The Gallerist	Comanchería: The Rise and Fall of the Comanche Empire	The Ruhr: A Story of Coal Trade	CO₂: Second Chance	Pax Pamir: Second Edition
8	Space Cadets	Navajo Wars	Arkwright	Grand Austria Hotel	Scythe	Clans of Caledonia	Pax Emancipation	Sierra West
9	Robinson Crusoe: Adventures on the Cursed Island	Room 25	Irish Gauge	The Bloody Inn	Liberty or Death: The American Insurrection	Lisboa	Forum Trajanum	Pipeline
10	Love Letter	Caverna: The Cave Farmers	Istanbul	The Voyages of Marco Polo	Jórvík	Twilight Imperium: Fourth Edition	Pandemic: Fall of Rome	Last Bastion
11	Tokaido	Bruges	Praetor	Churchill	Black Orchestra	Altiplano	TOKYO METRO	The Magnificent
12	Suburbia	Wildcatters	Camel Up	SteamRollers	Coal Baron: The Great Card Game	Here I Stand: 500th Anniversary Edition	Carpe Diem	Barrage
13	Kingdom of Solomon	Rococo	Imperial Settlers	DRCongo	The Oracle of Delphi	Merlin	Arkham Horror (Third Edition)	Hellenica: Story of Greece
14	Wallenstein (Second Edition)	Lewis & Clark: The Expedition	Belle of the Ball	Triumph & Tragedy: European Balance of Power 1936-1945	Citadels	Notre Dame: 10th Anniversary	Hitler's Reich: WW2 in Europe	Crystal Palace
15	Virgin Queen	The Hunters: German U-Boats at War, 1939-43	Roll Through the Ages: The Iron Age	Taluva Deluxe	Flamme Rouge	Time of Crisis: The Roman Empire in Turmoil, 235-284 AD	The Estates	Tiny Towns
16	CO₂	Bruxelles 1893	Nations: The Dice Game	Through the Ages: A New Story of Civilization	Great Western Trail	878 Vikings: Invasions of England	Rising Sun	Amul
17	Archipelago	1862: Railway Mania in the Eastern Counties	1944: Race to the Rhine	Copper Country	Pax Renaissance	Wendake	Crown of Emara	Bios: Origins (Second Edition)
18	Clash of Cultures	Rialto	Roll for the Galaxy	Porta Nigra	Arkham Horror: The Card Game	Dinosaur Island	Cosmic Encounter: 42nd Anniversary Edition	Gandhi: The Decolonization of British India, 1917 – 1947
19	1989: Dawn of Freedom	The Little Prince: Make Me a Planet	Greenland	Trickerion: Legends of Illusion	Forged in Steel	Coal Country	New Frontiers	Marco Polo II: In the Service of the Khan
20	Divided Republic	1775: Rebellion	Panamax	My Village	Pandemic: Iberia	Heaven & Ale	Tierra y Libertad: The Mexican Revolution Game (Second Edition)	Caylus 1303
21	Ginkgopolis	Terror in Meeple City	Patchwork	Shogun Big Box	Codenames: Pictures	Summit: The Board Game	AuZtralia	Coloma
22	Le Havre: The Inland Port	Rebel Raiders on the High Seas	Akrotiri	Neanderthal	Silent Victory: U.S. Submarines in the Pacific, 1941-45	Codenames: Disney – Family Edition	Brass: Birmingham	Fields of Fire 2
23	Android: Netrunner	A Distant Plain	Pandemic: The Cure	The King Is Dead	Vinhos Deluxe Edition	Lignum (Second Edition)	Donning the Purple	The Isle of Cats
24	Merchant of Venus (Second Edition)	Bora Bora	Subdivision	Pax Pamir	Turin Market	Spirit Island	Blackout: Hong Kong	Aftermath
25	Kairo	Francis Drake	Castles of Mad King Ludwig	Lignum	Cottage Garden	Sagrada	Cataclysm: A Second World War	The Quest for El Dorado: The Golden Temples

3.5 Interactive Table

This is an interactive table for the model’s predictions for the training set (from resampling).

4 Validating the Model

We’ll validate the model by looking at its predictions for games published in 2020. That is, how well did a model trained on a user’s collection through 2020 perform in predicting games for the user in 2020?

4.1 Model Assessment

username	outcome	dataset	method	.metric	.estimate
nakedmeeple	owned	validation	GLM	roc_auc	0.923
nakedmeeple	owned	validation	Decision Tree	roc_auc	0.883

4.2 Top Games from Validation Set

Table of top 50 games from 2020, highlighting games that the user owns.

Published	ID	Name	Pr(Owned)	Owned
2020	184267	On Mars	0.959	yes
2020	300322	Hallertau	0.934	yes
2020	253506	Versailles 1919	0.928	yes
2020	272739	Clinic: Deluxe Edition	0.902	yes
2020	297486	Ride the Rails	0.700	yes
2020	281655	High Frontier 4 All	0.685	no
2020	300877	New York Zoo	0.680	no
2020	316377	7 Wonders (Second Edition)	0.587	no
2020	292333	Cowboys II: Cowboys & Indians Edition	0.585	no
2020	318983	Faiyum	0.574	no
2020	304420	Bonfire	0.572	no
2020	206480	Imperial Struggle	0.550	yes
2020	242520	All Bridges Burning: Red Revolt and White Guard in Finland, 1917-1918	0.515	yes
2020	189664	The Hunted: Twilight of the U-Boats, 1943-45	0.514	no
2020	245224	La Belle Époque	0.501	no
2020	300001	Renature	0.479	no
2020	314040	Pandemic Legacy: Season 0	0.479	no
2020	310442	Feierabend	0.452	no
2020	265784	Cleopatra and the Society of Architects: Deluxe Edition	0.442	no
2020	300327	The Castles of Tuscany	0.435	no
2020	299179	Chancellorsville 1863	0.434	no
2020	276386	Caesar: Rome vs. Gaul	0.425	yes
2020	255456	Beneath the Med: Regia Marina at Sea 1940-1943	0.392	no
2020	312251	Curious Cargo	0.371	yes
2020	246900	Eclipse: Second Dawn for the Galaxy	0.361	no
2020	256317	Guild Master	0.345	no
2020	294788	Conqueror: Final Conquest	0.345	no
2020	306481	Tawantinsuyu: The Inca Empire	0.333	no
2020	284742	Honey Buzz	0.331	no
2020	320819	Dinner in Paris	0.329	no
2020	308765	Praga Caput Regni	0.319	yes
2020	301919	Pandemic: Hot Zone – North America	0.317	no
2020	286021	Free Market: NYC	0.317	no
2020	316554	Dune: Imperium	0.314	no
2020	284378	Kanban EV	0.307	yes
2020	319966	The King Is Dead: Second Edition	0.291	yes
2020	306040	Merv: The Heart of the Silk Road	0.289	no
2020	233262	Tidal Blades: Heroes of the Reef	0.286	no
2020	315631	Santorini: New York	0.262	no
2020	298572	Cosmic Encounter Duel	0.246	no
2020	284217	Rush M.D.	0.237	no
2020	269810	Nevada City	0.234	no
2020	267009	Rome & Roll	0.233	no
2020	296151	Viscounts of the West Kingdom	0.204	no
2020	317985	Beyond the Sun	0.203	yes
2020	282954	Paris	0.199	no
2020	301716	Glasgow	0.198	no
2020	282922	Windward	0.198	no
2020	318084	Furnace	0.198	yes
2020	291457	Gloomhaven: Jaws of the Lion	0.197	no

5 Predicting Upcoming Games

We can then refit our model to the training and validation set in order to predict all upcoming games for the user.

5.1 Top Upcoming Games

Examine the top 100 upcoming games, highlighting in blue ones the user already owns.

Published	ID	Name	Pr(Owned)	Owned
2021	343905	Boonlake	0.988	no
2021	342942	Ark Nova	0.853	no
2022	310873	Carnegie	0.849	no
2021	344277	Corrosion	0.843	no
2022	349793	Age of Rome	0.758	no
2022	314580	Hamburg	0.688	no
2021	338760	Imperial Steam	0.661	no
2021	262941	Dominant Species: Marine	0.658	yes
2021	339484	Savannah Park	0.640	no
2021	325022	Coffee Traders	0.618	no
2021	325698	Juicy Fruits	0.602	no
2021	281248	Cape May	0.566	no
2023	312959	Rallyman: DIRT	0.566	no
2021	338980	Eastern Empires	0.505	no
2021	292899	Tribune	0.471	no
2021	206509	Bayonets & Tomahawks	0.422	yes
2021	277700	Merchants Cove	0.408	no
2021	291859	Riftforce	0.407	no
2022	326945	Castles of Mad King Ludwig: Collector's Edition	0.397	no
2021	296577	Red Flag Over Paris	0.387	yes
2021	283387	Rocketmen	0.360	no
2022	304051	Creature Comforts	0.347	no
2021	249277	Brazil: Imperial	0.346	no
2021	298102	Roll Camera!: The Filmmaking Board Game	0.343	no
2021	326804	Rorschach	0.337	no
2021	308119	Pax Renaissance: 2nd Edition	0.335	no
2021	300323	Conquest & Consequence	0.312	no
2022	322499	Red Dust Rebellion	0.312	no
2021	251747	Atlantic Chase	0.304	yes
2022	300192	Twilight Struggle: Red Sea – Conflict in the Horn of Africa	0.299	no
2022	284189	Foundations of Rome	0.294	no
2021	196676	Rome, Inc.: From Augustus to Diocletian	0.290	no
2021	341169	Great Western Trail (Second Edition)	0.287	no
2021	304985	Dark Ages: Holy Roman Empire	0.284	no
2021	295535	Dark Ages: Heritage of Charlemagne	0.284	no
2022	291155	Enemy Action: Kharkov	0.284	no
2021	308989	Bristol 1350	0.272	no
2021	319792	Fly-A-Way	0.264	no
2022	295103	Almoravid: Reconquista and Riposte in Spain, 1085-1086	0.264	no
2021	318709	For Sale Autorama	0.263	no
2021	303954	Pax Viking	0.263	no
2022	280726	Legacies	0.263	no
2022	309913	Border Reivers: Anglo-Scottish Border Raids, 1513-1603	0.262	no
2022	176588	A Glorious Chance: The Naval Struggle for Lake Ontario in the War of 1812	0.251	no
2021	238799	Messina 1347	0.244	no
2022	350205	Horseless Carriage	0.232	no
2022	354254	Voices In My Head	0.224	no
2021	290236	Canvas	0.219	no
2022	283137	Human Punishment: The Beginning	0.214	no
2022	266018	Trinidad	0.214	no
2021	314088	Agropolis	0.213	no
2021	298378	Maharaja	0.209	no
2022	305096	Endless Winter: Paleoamericans	0.207	no
2021	323156	Stroganov	0.201	no
2021	344768	Mobile Markets: A Smartphone Inc. Game	0.201	no
2022	331106	The Witcher: Old World	0.199	no
2023	347909	Rogue Angels: Legacy of the Burning Suns	0.195	no
2022	326175	The Smoky Valley	0.194	no
2021	320960	Roll In One	0.193	no
2022	330950	Age of Galaxy	0.189	no
2021	339958	Gutenberg	0.184	no
2021	286439	Import / Export: Definitive Edition	0.178	no
2021	324242	Sheepy Time	0.175	no
2022	305462	The Age of Atlantis	0.175	no
2021	341048	Free Ride	0.174	no
2021	260524	Beyond Humanity: Colonies	0.173	no
2022	190572	1941: Race to Moscow	0.172	no
2021	305761	Whale Riders	0.172	no
2021	292375	The Great Wall	0.172	no
2022	325096	Skies Above Britain	0.170	no
2022	233958	Plains Indian Wars	0.169	no
2021	252752	Genotype: A Mendelian Genetics Game	0.164	no
2021	329591	Ultimate Railroads	0.164	no
2022	347703	First Rat	0.163	no
2021	259962	Stress Botics	0.159	no
2021	322195	Kokopelli	0.154	no
2021	274861	Venice	0.151	no
2021	298069	Cubitos	0.151	no
2021	299684	Khôra: Rise of an Empire	0.151	no
2021	285967	Ankh: Gods of Egypt	0.151	no
2021	292126	Excavation Earth	0.148	no
2022	275215	Namiji	0.148	no
2021	259066	Commands & Colors: Samurai Battles	0.145	yes
2022	294880	Chai: Tea for 2	0.144	no
2021	339906	The Hunger	0.144	no
2022	317511	Tindaya	0.144	no
2021	314393	Wutaki	0.141	no
2021	326848	Illumination	0.140	yes
2021	328871	Terraforming Mars: Ares Expedition	0.139	no
2022	318450	Bios: Mesofauna	0.139	no
2021	301366	Caves of Rwenzori	0.139	no
2022	324090	Scarface 1920	0.137	no
2021	328569	Mint Bid	0.131	no
2021	329670	Pandemic: Hot Zone – Europe	0.131	no
2021	259394	Storm Above the Reich	0.131	no
2022	300217	Merchants of the Dark Road	0.130	no
2021	258242	Magnate: The First City	0.128	no
2022	322524	Bardsung	0.127	no
2022	319807	Shogun no Katana	0.126	no
2022	237179	Weather Machine	0.126	no

Analyzing Individual BGG Users